Telomere length (TL) is associated with several aging-related diseases. Here, we present a DNA methylation estimator of TL (DNAmTL) based on 140 CpGs. Leukocyte DNAmTL is applicable across the entire age spectrum and is more strongly associated with age than measured leukocyte TL (LTL) (r ~-0.75 for DNAmTL versus r ~ -0.35 for LTL). Leukocyte DNAmTL outperforms LTL in predicting: i) time-to-death (p=2.5E-20), ii) time-to-coronary heart disease (p=6.6E-5), iii) time-to-congestive heart failure (p=3.5E-6), and iv) association with smoking history (p=1.21E-17). These associations are further validated in large scale methylation data (n=10k samples) from the Framingham Heart Study, Women's Health Initiative, Jackson Heart Study, InChianti, Lothian Birth Cohorts, Twins UK, and Bogalusa Heart Study. Leukocyte DNAmTL is also associated with measures of physical fitness/functioning (p=0.029), age-at-menopause (p=0.039), dietary variables (omega 3, fish, vegetable intake), educational attainment (p=3.3E-8) and income (p=3.1E-5). Experiments in cultured somatic cells show that DNAmTL dynamics reflect in part cell replication rather than TL per se. DNAmTL is not only an epigenetic biomarker of replicative history of cells, but a useful marker of age-related pathologies that are associated with it.

Personality-outcome associations, typically represented using the Big Five personality domains, are ubiquitous, but often weak and possibly driven by the constituents of these domains. We hypothesized that representing the associations using personality questionnaire items (as markers for personality nuances) could increase prediction strength. Using the National Child Development Study (N = 8719), we predicted 40 diverse outcomes from both the Big Five domains and their 50 items. Models were trained (using penalized regression) and applied for prediction in independent sample partitions (with 100 permutations). Item models tended to out-predict Big Five models (explaining on average 30% more variance), regardless of outcomes' independently rated breadth versus behavioural specificity. Moreover, the predictive power of Big Five domains per se was at least partly inflated by the unique variance of their constituent items, especially for generally more predictable outcomes. Removing the Big Five variance from items marginally reduced their predictive power. These findings are consistent with the possibility that the associations of personality with outcomes often pertain to (potentially large numbers of) specific behavioural, cognitive, affective, and motivational characteristics represented by single questionnaire items rather than to the broader (underlying) traits that these items are ostensibly indicators of. This may also have implications for personality-based interventions.

Although plasma proteins may serve as markers of neurological disease risk, the molecular mechanisms responsible for inter-individual variation in plasma protein levels are poorly understood. Therefore, we conduct genome- and epigenome-wide association studies on the levels of 92 neurological proteins to identify genetic and epigenetic loci associated with their plasma concentrations (n = 750 healthy older adults). We identify 41 independent genome-wide significant (P < 5.4 × 10 −10 ) loci for 33 proteins and 26 epigenome-wide significant (P < 3.9 × 10 −10 ) sites associated with the levels of 9 proteins. Using this information, we identify biological pathways in which putative neurological biomarkers are implicated (neurological, immunological and extracellular matrix metabolic pathways). We also observe causal relationships (by Mendelian randomisation analysis) between changes in gene expression (DRAXIN, MDGA1 and KYNU), or DNA methylation profiles (MATN3, MDGA1 and NEP), and altered plasma protein levels. Together, this may help inform causal relationships between biomarkers and neurological diseases.

Individuals of the same chronological age exhibit disparate rates of biological ageing. Consequently, a number of methodologies have been proposed to determine biological age and primarily exploit variation at the level of DNA methylation (DNAm). A novel epigenetic clock, termed 'DNAm GrimAge' has outperformed its predecessors in predicting the risk of mortality as well as many age-related morbidities. However, the association between DNAm GrimAge and cognitive or neuroimaging phenotypes remains unknown. We explore these associations in the Lothian Birth Cohort 1936 (n = 709, mean age 73 years). Higher DNAm GrimAge was strongly associated with all-cause mortality over the eighth decade (Hazard Ratio per standard deviation increase in GrimAge: 1.81, P < 2.0 × 10 −16). Higher DNAm GrimAge was associated with lower age 11 IQ (β = −0.11), lower age 73 general cognitive ability (β = −0.18), decreased brain volume (β = −0.25) and increased brain white matter hyperintensities (β = 0.17). There was tentative evidence for a longitudinal association between DNAm GrimAge and cognitive decline from age 70 to 79. Sixty-nine of 137 health-and brain-related phenotypes tested were significantly associated with GrimAge. Adjusting all models for childhood intelligence attenuated to non-significance a small number of associations (12/69 associations; 6 of which were cognitive traits), but not the association with general cognitive ability (33.9% attenuation). Higher DNAm GrimAge associates with lower cognitive ability and brain vascular lesions in older age, independently of early-life cognitive ability. This epigenetic predictor of mortality associates with different measures of brain health and may aid in the prediction of age-related cognitive decline.

The finer details? The predictability of life outcomes from Big Five domains, facets, and nuances Associations between personality traits and life outcomes are usually studied using the Big Five domains and, occasionally, their facets. But recent research suggests these associations may be driven by the items (reflecting nuances) chosen to measure these traits. Using a large dataset (N = 6,126), we examined associations with 53 self-reported outcomes using domains, facets and items (markers for nuances), training and validating models in different sample partitions. Facets better predicted outcomes than domains (on average, 18.0% vs 16.6% of variance explained), but items provided the most accurate predictions (on average 20.9%). Removing domain and facet variance from items had no effect on their predictive validity, suggesting that outcome-related information was present in items' unique variances (nuances). Item-based prediction also showed the highest outcome-specificity (discriminant validity). These observations, replicating previous indications, suggest that personality traits' associations with outcomes are often driven by narrow personality nuances.

Individuals of the same chronological age exhibit disparate rates of biological ageing.Consequently, a number of methodologies have been proposed to determine biological age and primarily exploit variation at the level of DNA methylation (DNAm) -a commonly studied epigenetic mechanism. A novel epigenetic clock, termed 'DNAm GrimAge' has outperformed its predecessors in predicting the risk of mortality as well as a number of age-related morbidities. However, the association between DNAm GrimAge and cognitive or neuroimaging phenotypes remains unknown. We explore these associations in the Lothian Birth Cohort 1936 (n=709, mean age 73 years). Higher DNAm GrimAge was strongly associated with all-cause mortality over twelve years of follow-up (Hazard Ratio per standard deviation increase in GrimAge: 1.81, P < 2.0 x 10 -16 ). Higher DNAm GrimAge was associated with lower age 11 IQ (β=-0.11), lower age 73 general cognitive ability (β=-0.18), decreased brain volume (β=-0.25) and increased brain white matter hyperintensities (β=0.17). Sixtyeight of 137 health-and brain-related phenotypes tested were significantly associated with DNAm GrimAge. Adjusting all models for childhood cognitive ability attenuated to nonsignificance a small number of associations (12/68 associations; 6 of which were cognitive traits), but not the association with general cognitive ability (33.9% attenuation). Higher DNAm GrimAge cross-sectionally associates with lower cognitive ability and brain vascular lesions in older age, independently of early life cognitive ability. Thus, this epigenetic predictor of mortality is also associated with multiple different measures of brain health and may aid in the prediction of age-related cognitive decline.

Telomere length is associated with age-related diseases and is highly heritable. It is unclear, however, to what extent epigenetic modifications are associated with leukocyte telomere length (LTL). In this study, we conducted a large-scale epigenome-wide association study (EWAS) of LTL using seven large cohorts (n=5,713) – the Framingham Heart Study, the Jackson Heart Study, the Women’s Health Initiative, the Bogalusa Heart Study, the Lothian Birth Cohorts of 1921 and 1936, and the Longitudinal Study of Aging Danish Twins. Our stratified analysis suggests that EWAS findings for women of African ancestry may be distinct from those of three other groups: males of African ancestry, and males and females of European ancestry. Using a meta-analysis framework, we identified DNA methylation (DNAm) levels at 823 CpG sites to be significantly associated (P<1E-7) with LTL after adjusting for age, sex, ethnicity, and imputed white blood cell counts. Functional enrichment analyses revealed that these CpG sites are near genes that play a role in circadian rhythm, blood coagulation, and wound healing. Weighted correlation network analysis identified four co-methylation modules associated with LTL, age, and blood cell counts. Overall, this study reveals highly significant relationships between two hallmarks of aging: telomere biology and epigenetic changes.

Background: DNA methylation outlier burden has been suggested as a potential marker of biological age. An outlier is typically defined as DNA methylation levels at any one CpG site that are three times beyond the interquartile range from the 25th or 75th percentiles compared to the rest of the population. DNA methylation outlier burden (the number of such outlier sites per individual) increases exponentially with age. However, these findings have been observed in small samples. Results: Here, we showed an association between age and log 10 -transformed DNA methylation outlier burden in a large cross-sectional cohort, the Generation Scotland Family Health Study (N = 7010, β = 0.0091, p < 2 × 10 −16 ), and in two longitudinal cohort studies, the Lothian Birth Cohorts of 1921 (N = 430, β = 0.033, p = 7.9 × 10 −4 ) and 1936 (N = 898, β = 0.0079, p = 0.074). Significant confounders of both cross-sectional and longitudinal associations between outlier burden and age included white blood cell proportions, body mass index (BMI), smoking, and batch effects. In Generation Scotland, the increase in epigenetic outlier burden with age was not purely an artefact of an increase in DNA methylation level variability with age (epigenetic drift). Log 10 -transformed DNA methylation outlier burden in Generation Scotland was not related to self-reported, or family history of, age-related diseases, and it was not heritable (SNP-based heritability of 4.4%, p = 0.18). Finally, DNA methylation outlier burden was not significantly related to survival in either of the Lothian Birth Cohorts individually or in the meta-analysis after correction for multiple testing (HR meta = 1.12; 95% CI meta = [1.02; 1.21]; p meta = 0.021).Conclusions: These findings suggest that, while it does not associate with ageing-related health outcomes, DNA methylation outlier burden does track chronological ageing and may also relate to survival. DNA methylation outlier burden may thus be useful as a marker of biological ageing.